Game optimization system

ABSTRACT

A game optimization system is disclosed. The game optimization system may take the form of a game balancing engine that is able to both monitor and identify components of games that form dominant and/or weak strategies. If desired, the game optimization system may further make or suggest changes to the game in order to bring out-of-balance components into balance.

PRIORITY CLAIM

The present application claims priority to U.S. Provisional PatentApplication Ser. No. 60/682954, filed May 20, 2006, the entirety ofwhich is hereby incorporated by reference for all purposes.

BACKGROUND

Games have always been a popular pastime. Of late, computer gaming hasbecome an important part of the game world. Computer networks such asthe internet allow players on different computers in different locationsto play with each other in real time.

Many popular on-line games involve the selection and use of multiplegame elements, or components, that a player manipulates in order tosucceed in the game, typically by defeating an opponent and/oraccomplishing one or more tasks. Examples of games includingplayer-selected game components include, but are not limited to,collectible card games (CCGs), role playing games (RPGs), and real timestrategy games (RTS).

In contrast to games like chess, checkers, or hearts, where the playingcomponents are static (pre-determined pieces with pre-determinedcharacteristics), in the CCG and RPG-style games, players make choicesregarding which playing components they will use in order to play anygiven game. For example, in one style of CCGs, players typicallypurchase (or trade for) large numbers of cards from which they are ableto design and build their own customized deck(s). The player then usesthe customized deck to battle one or more opponents, typically byplaying combinations of cards and engaging in various duels. Thus, theplayer chooses which playing components he or she wishes to use. In onestyle of RPGs, players typically create one or more characters havingvarious characteristics (strength, agility, intelligence, etc.) and thentravel through the game collecting various game components, which mayinclude, without limitation, tangible and intangible components such asabilities, spells, weapons, items, etc. that help the player's characterbattle opponents, accomplish tasks, and/or otherwise progress throughthe game. Thus, like the CCGs, RPG players often make choices regardingsome or all of the components with which they play the game. Moreover,in many RPGs, the character in the RPG is limited to only a certainnumber of items or game components and must, therefore, select frombetween several different items, thereby forcing the player to makechoices during the game regarding the items or game components withwhich he or she wishes to play.

Currently, thousands or even hundreds of thousands of players are ableto access and play on-line games. As a game is played more and more, itmay become apparent that, despite all efforts of the game designers, aparticular game component strategy, by which is meant the use of aparticular game component or a particular combination of game componentsin game play, unfairly dominates the game. In the CCG context, adominant strategy may become apparent by the repeated, non-randomappearance of one or more specific cards in a statistically significantnumber of winning decks. In the RPG context, a dominant strategy maybecome apparent by the repeated, non-random appearance of one or morecharacters having given characteristics, and/or selecting similarabilities, and/or the ownership and/or use of one or more items, bysuccessful players. Conversely, it may become apparent that there are(weak) strategies which are nearly always unsuccessful.

Thus, in the context of the present disclosure, the existence ofdominant and weak strategies essentially becomes a requirement thatplayers who wish to “win” or be successful limit their playing componentchoices to those components that are dominant and avoid those componentsthat are weak. Because these types of games are designed and intended toallow players to make choices regarding game strategy and devise theirown unique strategies, significant limitations on the choices thatplayers make can negatively impact enjoyment of the game. Accordingly,many game designers spend large amounts of time during game developmentattempting to balance the game. However, because such efforts are madeduring game design and, typically, before the game is played by thegeneral public, these efforts often ultimately fail, as it is often onlyafter extensive game play that unfairly dominant and weak strategiesbecome apparent.

Thus, a game that is designed to avoid the presence of unfairly dominantor weak strategies is greatly desirable. Therefore, a system that isable to both monitor for and identify game components that form or leadto the presence of unfairly dominant or weak strategies is greatlydesired. Moreover, a system that is able to dynamically adjust the game,in order to account for and counteract any unfairly dominant or weakstrategies is similarly greatly desired.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic illustration of one embodiment of a game balancingsystem for networked game play according to the present disclosure.

FIG. 2 is a schematic illustration of one embodiment of a game balancingsystem for non-networked game play according to the present disclosure

FIG. 3 is a flowchart depicting a first embodiment of a game balancingengine according to the present disclosure.

FIG. 4 is a flowchart depicting a second embodiment of a game balancingengine according to the present disclosure.

FIG. 5 is a flowchart depicting a third embodiment of a game balancingengine according to the present disclosure.

FIG. 6 depicts an exemplary playing piece according to one embodiment ofa game according to the present disclosure.

FIG. 7 depicts an exemplary playing field according to one embodiment ofa game according to the present disclosure.

DETAILED DESCRIPTION

The present disclosure describes a game balancing engine (GBE) that isable to both monitor and identify components of games that form dominantor weak strategies. In its most basic embodiment, the GBE comprises acomputer program that monitors game play and measures the usage of theindividual game components in order to identify those game componentsthat create an unfair advantage or unfair disadvantage to a player usingthose components in game play.

For the purposes of the present disclosure it will be understood thatthe following terms are defined as follows:

“Game system” includes any hardware system by which the game iscommunicated to the player. The game system may be a dedicated singlegame system (Plug it in and Play TV Games, Jakks Pacific, Malibu,Calif.), a dedicated multi-game system (e.g. the Play Station & PlayStation 2 game systems from Sony Co.; the X box game system fromMicrosoft Corp.; or the Game Boy, Nintendo, and Nintendo 64 game systemsfrom Nintendo Corp.), or a general or multi-purpose device capable ofplaying games such as a personal computer, cellular phone, personal dataassistant (PDA), handheld computer, or the like. It should be noted thatthe software and/or code for playing the game need not reside locally onthe game system. Thus a computer that links to the internet and allows aplayer to play a game that resides entirely on a separate server wouldstill be considered a game system for the purposes of the presentdisclosure.

“Networked game play” includes all ways and methods by which two or moregame systems can communicate or link with one another, for example, inorder to allow two or more players to interact with one another or thesame environment. Networked game play may take place whether or not theplayers play “against” one another. Thus, networked game play includesgames in which player vs. player combat is strictly banned, as well ascooperative play games and traditional player vs. player combat games.Networked game play includes, but is not limited to, both private andpublic internet and intranet game play.

“Non-networked game play” includes any game play that is not networkedgame play. Accordingly, non-networked game play may include, withoutlimitation, stand alone games played on a single computer, or on-linesingle player games that do not involve communication, linkage, orinteraction with other players or shared game environments.

“Game component” includes any tangible or intangible element existing inthe game that a player may choose to acquire and/or use. Examples ofgame components include, without limitation, skills, items, cards,spells, characteristics, personality traits, the right to go first ormake a move, and the like. In other words, game components are amanifestation of the strategic choices a player makes between two ormore game elements. Thus, a game component may further include paths,routes, rooms, actions, etc. where a player is presented with the choicebetween whether to take path A or path B, whether to engage in action Aor action B, or whether to take path A or engage in action A, etc.

As stated above, according to one embodiment, the GBE of the presentdisclosure is intended to reduce or eliminate the existence of unfairlyadvantageous or disadvantageous strategies in games, thereby encouragingstrategic diversity and more interesting game play.

Exemplary game balancing systems according to the present disclosure areshown in FIGS. 1 and 2. In FIG. 1, game balancing system 100 is used tobalance networked game play. In this particular example, a server 102 isin electronic communication with personal computers 104 and 106. Server102 and computers 104 and 106 are capable of cooperatively running agame 108. The code for game 108 may reside on server 102, computer 104,computer 106, or a combination of any of the above. Moreover, it will beappreciated that either computer 104 or 106 may act as a server. In theembodiment shown in FIG. 1, GBE 110, resides on server 102. However, asshown with dashed lines, it will be appreciated that GBE 110 may residein an alternate location and simply collect game play data from server102, computer 106 and/or computer 108. Moreover, it will further beappreciated that while not shown in the Figure, some or all of GBE 110may reside on either computer 104 or computer 106. In this system, gameplay data may be collected by the GBE during or after game play.

In FIG. 2, game balancing system 200 is used to balance non-networkedgame play. In this particular example, personal computers 202 and 204each independently run a computer game 206 a and 206 b, respectively.Personal computers 202 and 204 are each capable of communicating with aGBE 208 located at a distant location, such as a personal computer orserver. Computers 202 and 204 are not necessarily in communication withone another. Furthermore, as shown by broken line 210, games 206 a and206 b are not necessarily in communication with each other. Game playdata on each of computer 202 and 204 is received by the GBE during orafter game play.

As shown in FIG. 3, in one particular method, the GBE collects dataregarding actual game play in order to monitor usage of the various gamecomponents in the game. The GBE then determines the acceptable usagerange for each monitored game component and identifies those componentsfor which usage falls outside of a set of predetermined acceptableparameters. The game is then adjusted to encourage the usage of out ofbalance game components back to within the acceptable range. Theadjustment may be performed automatically by the GBE, in which case thegame designer may or may not be alerted as to which game components wereout of balance. Alternatively, the GBE may identify out of balance gamecomponents to the game designer, who then adjusts the game accordingly.

As briefly discussed above, data collection may take place at any time.As non-limiting examples, data may be collected in real time, (i.e. asthe game is being played), actively sent to the GBE by players uponcompletion of a game, or periodically uploaded by the GBE at random orpredetermined intervals.

The GBE described in the present disclosure is suitable for use with awide variety of game types including, but not limited to, collectiblecard games (CCGs), role playing games (RPGs) and Real Time StrategyGames (RTSs).

As a simple example of a GBE suitable for use with a CCG, the GBE maymonitor how often players incorporate particular cards in theirpersonalized decks. If the GBE identifies a particular card that isbeing used in a higher proportion of player decks than defined by thegame designers as being acceptable, the GBE can label the card as beingout of balance and alert the game designer to the fact. The gamedesigner can then alter the out of balance card in any number of ways,for example by making the card more expensive or harder to use, reducingthe effects of using the card, or making a new card available that ismore effective in counteracting the effects of the out of balance card.

Alternatively, instead of simply alerting the game designer to theexistence of the out-of-balance card, the GBE may be instructed toautomatically adjust one or more specific features of any cardidentified as being out of balance (i.e. by increasing the card's cost,reducing the card's effects, etc.). Accordingly, the GBE may be providedwith a list of parameters by which a card may be out of balance and aset of solutions, an example of which is shown in the following chart:Out of balance usage Solutions Present in 90%-100% of decks Increasecost by 100% -or- Decrease power by factor of 2 Present in 80-89% ofdecks Increase cost by 75% -or- Decrease power by factor of 1.5 Presentin 70-79% of decks Increase cost by 50% -or- Decrease power by factor of1

In the above chart, the GBE has been provided with two solutions foreach out of balance scenario. Thus the computer may elect one of thesolutions based at random or based on an algorithm of the designerschoosing. Of course it will be understood that the above chart isintended solely for the purpose of description and understanding of thedisclosure and should not be considered as limiting in any sense. Itwill also be understood that in many CCGS, there are often cards thatmust be present in all decks. Thus, in some cases, whether or not a cardis out of balance and the possible solution(s) for fixing the cardimbalance may be determined on a card-by-card basis.

In contrast to many CCGS, where the players' choices regarding whichcards to include in their deck are made before game play starts, in manyRPGS, players are often required to make choices involving gamecomponents during the game. For example, a player may be allowed tocollect a certain number of items throughout the course of the game.Often, the number of items a particular player may have in his or herpossession at any one time is limited, either by specific rules (i.e.each player can have a maximum of 5 items), by current circumstances(player X has $10 to spend, there are four items available for purchasein the store, but each item in the store costs $5), or by a combinationof the rules and circumstances. Thus, each player is forced to choosewhich specific item(s) he or she wishes to use in the game.Alternatively, a player may simply elect to trade away or sell aparticular component. These choices can be monitored by the GBE todetermine whether specific items are being chosen more frequently thanis desirable. Thus, when item X, costing $5 is consistently chosen overitem Y, which also costs $5, and the game designers intended for the twoitems to be roughly equivalent in their impact on the game, the GBE mayidentify items X and Y as being out of balance.

FIG. 4 provides another method for implementing the GBE of the presentdisclosure. In this method, each player's usage statistics are weightedby a success calculation. As a simplistic example, the successcalculation may be determined by whether the player was successful ornot successful in the game when in the possession of a particular gamecomponent. Typically, a component will have to be part of a successfulgame in order to be part of the data set used to determine whether ornot the component is in balance. The definition of “successful” usagemay differ from game to game and as desired by the game designer. Forexample, in a CCG, a card may be required to be part of a winning deckin order for that card to be labeled as having been used successfully,therefore making the usage of that card acceptable for data collectionpurposes. Alternatively, in an RPG where the goal is often to completeone or more tasks, “successful implementation” may be identified when aplayer succeeds in a task or advances to a new level. One advantage ofthis method is that it reduces the possibility that a game player mightintentionally lose with a given strategy in order to trick the GBE intoaltering one or more game components.

Alternatively, the GBE may be designed to factor in a player's degree ofsuccess during a game in calculating whether or not a component is outof balance. In this example, rather than using binary calculation(successful or unsuccessful) to determine whether a particular player'sgame components should be included in the GBE calculation, a player'sdegree of success is used as a factor to determine the representationalrelevance of that player's component usage. For example, the datagenerated by a player who enters a game for 10 seconds and gains 5experience points may be less representationally relevant than a playerwho enters a game for 100 hours and gains 1 million experience points.However, using the degree of success calculation, the 10 second/5experience point player's data may still be statistically significantand thus should be included in the GBE calculation, but would simplycarry less weight than the 100 hour/1 million experience point player'sdata. Other ways of determining degree of success include progressionthrough the game (i.e level or other advancement), number of wins,win/loss record, time spent playing the game, player rankings orratings, and the like.

Those familiar with games will be aware that in many, if not most,games, it will be expected that some game components will be used morefrequently than others, and the game will purposefully be designed assuch. In such situations, it is desirable to ensure that game pieces arebeing used “fairly,” but not necessarily desirable that game componentsbe used equally. As described above, in this context the term “fair use”is intended to mean that no one particular strategy, or a small set ofstrategies, become so dominant that a player must adopt one of thosestrategies in order to be competitive. One method of ensuring fair useis by calculating the relative expected usage (REU) of each componentand then factoring in the REU of the component when determining whetherthe component is, in fact, out of balance.

A basic example of a GBE incorporating REU is shown in FIG. 5. Accordingto FIG. 5, the GBE initially monitors usage of each game component. TheGBE then weights each player's usage by that player's degree of success.In combination with the degree of success weighting, the GBE factors inthe REU to determine whether the usage was within acceptable parameters.If the usage was outside of acceptable parameters, the GBE identifiesout of balance components to the game designers and/or adjusts one ormore features of the game components or game rules.

In general, REU describes the likelihood of a game component beingencountered and used by a particular player during a particular game, asdesired by the game designers. For example, game designers will oftencreate very powerful game components, somewhat powerful game components,and weak game components. (It will be understood, of course, that thesecategories are created for the ease of description and that commonlygame components will fall along a sliding scale of strength.) Thesecomponent categories typically differ in some way in an attempt tobalance their usage. One method for attempting to balance the usage ofmore and less powerful components is to limit the public distribution ofthe more powerful cards (i.e. rare cards in CCGs.) However, thisbalancing technique does not necessarily guarantee fair game play, asdedicated gamers will typically purchase any rare card(s) they desire,no matter what the cost—often forcing other players who would like to becompetitive to purchase the same card(s) and adopt the same strategies.Other methods for balancing these component categories include makingvery powerful game components more costly, requiring a higher skilllevel to play the very powerful game components, or making the morepowerful game components more difficult to use.

According to one embodiment of the present disclosure, REU provides amethod by which one can determine specifically how to adjustout-of-balance game components by reverse engineering actual games anddetermining probabilistically what component choices a given playerwould have made, had the game been balanced. More specifically, ExpectedUsage is a specific game by game, player by player, choice by choicecalculation of the probability, given all available knowledge about aparticular player, that this player would have used a specific componentif all the game components had an average marginal game value exactlyproportional to their cost. It will be appreciated that in this context,the term “cost” is applied broadly to mean whatever it is that a playermust do (pay money, pay points, acquire skills, etc.) in order toacquire and/or use the component. In other words, “cost” can be anychange in game state associated with using and/or acquiring thecomponent that has a negative effect on the player. Relative ExpectedUsage (REU) is any measure that is proportional to Expected Usage.

In general, there are at least three different types of components, eachhaving different types of costs that must be incorporated into the REUcalculation. These are pay-to-play components, skill-point acquiredcomponents, and effort-based components.

Pay-to-play components are components where a player must pay someamount of currency in order to play the component. These types ofcomponents are most commonly seen in CCG-type games, but may appear inother types of games. The amount paid for the component is intended tobe commensurate with the power level of the component. Thus, theexpectation in a hyper-balanced world (a world in which each componenthas an average marginal game value exactly proportional to its cost) isthat these components are used interchangeably. In such a case, the REUcalculation is essentially the availability calculation with someadjustment. The adjustment is related to the fact that players are nomore likely to use a component they have 1000 of than one they have 2of.

Skill-point acquired components are obtained by paying points, wherepoints are accumulated through the game as the player advances inlevels. These types of components are most commonly seen in RPG-typegame, but may be seen in any type of game. Similar to pay-to-playcomponents, the total point cost of the component is intended to becommensurate with the power level of the-component. However, becauseskill points are accumulated by level advancement, usage should becommensurate with power level. In other words, more powerful componentsare harder to obtain (as opposed to play). It will be appreciated thatin this context, the term “power” is applied broadly to mean whatever itis that a player gains upon using or acquiring the component. In otherwords, “power” can be any change in game state associated with usingand/or acquiring the component that has a positive effect on the player.For these types of components, the REU calculation may be based on theassumption that all possible skill-point paths should be used equally byall players who have the skill points required to access those paths.

Effort-based components use up some (limited) resource each time thecomponent is used. These types of components are commonly seen in bothCCG and RPG-type games. Often, effort-based components are abilities.The calculation of REU for effort-based components is very similar tothe calculation for pay-to-play components because the cost of usage (inthis case resource depletion) should be equivalent to the power of thecomponent. Thus, as with pay-to-play components, a hyper-balanced gamewould expect players to be indifferent between such components.

Of course it will be appreciated that it is not the goal of every gamedesigner to hyper-balance their games. Rather, the goal is generally toincrease strategic diversity by reducing or eliminating unfairlydominant or weak strategies. Thus, while the REU calculation may dependon what should or would have happened in a hyper-balanced game, thedetermination of whether a given component or set of components is, infact, out-of-balance is typically determined by a range of acceptable(or non-acceptable) divergences from the hyper-balanced scenario.

Of course it will be appreciated that the range of acceptable (ornon-acceptable) divergences from the hyper-balanced scenario may be acomponent-specific calculation. For example, a game designer may desirefor some components (or some choices) to be hyper-balanced, while othercomponents (or choices) need only fall into an acceptable range. As aspecific non-limiting example, a game may include the provision that theplayer who goes first is penalized by some amount. For example, theplayer going first may be required to pay some amount of currency forthe privilege of going first and/or not allowed to engage in certainactions or make certain choices during the first turn. However, the gamedesigner may desire for this choice to be hyper-balanced, such thatwhether or not a player goes first provides no advantage to eitherplayer.

In order to provide a more specific description of how REU may becalculated for a specific game, it is helpful to describe an exemplarygame suitable for use with a GBE employing an REU. It will be understoodthat the above-described game balancing system and method is applicableto a wide range of networked and non-networked games that utilizevarious game components, including, but not limited to, CCGS, RPGs,adventure games, racing games, etc. Thus, the example below is to betaken in a non-limiting sense as numerous variations and manifestationsare possible. Moreover, it will be understood that the game describedbelow may be played and appreciated independently of the GBE and shouldnot be considered as requiring the implementation of a GBE (with orwithout an REU calculation.)

One embodiment of the presently described game suitable for use with theabove-described GBE involves an online game that combines certainelements of card-based strategy games (CCGs) with other elements oflevel-based RPG's. In the most general sense, the game combines themechanic of each player custom-designing a collection of game components(i.e. cards) into his or her own arsenal of components (i.e. deck), butthen requires each player to progress through an experience system (i.e.different levels) in order to access subsequent content (i.e. expansioncards). As with most games, the present game may incorporate somecentralized theme in order to tell a story and generate increased playerinterest. An exemplary theme might be espionage. For the purpose of thepresent description, specific game examples will be provided withreference to the espionage theme. However, it will be understood thatthe game may incorporate any or no theme while retaining similar gamemechanics. Moreover, it will be appreciated that the game describedbelow may be implemented using only a subset of the game mechanicsdescribed below and/or incorporating additional game mechanics notincluded in the description below.

Typically, each player will initially create a character in the gamesystem. In order to create the character, the player may select from anumber of different traits, or foci. The number of traits that areselected may be limited by the game rules. For example, in a gameincorporating a total of seven distinct traits, each player may selecttwo characteristics for his or her character. In such a game, the playermay designate a primary trait and a secondary trait. Of course it willbe appreciated that the game may include a greater or lesser number oftraits overall and that each character may be allowed to select more orless than two traits for his or her character. Moreover, the game may bedesigned to allow different players to select different numbers oftraits.

According to one method of playing the game, the selected primary andsecondary traits dictates the set of game components that will beavailable to each player's character when the player is designing his orher character's arsenal. For example, in a game incorporating thefollowing foci: paramilitary, mastermind, corporate, psychic, rogue,science, and hacker; a player who selects the foci paramilitary andpsychic will have an entirely different set of game components fromwhich to design an arsenal than a player who selects the foci rogue andmastermind.

According to one method of playing the game, the objective of the gameis to sequentially complete a predetermined number of tasks. During gameplay, the players have the option of playing game components from theirindividually designed arsenals that prevent the opponent from completinghis or her task, playing game components from their individuallydesigned arsenals in an attempt to complete their own task, or both. Forexample, in an espionage-themed game, the game may be won bysequentially capturing three secrets from the opposing player. Duringgame play, the players have the option of playing game components fromtheir arsenals that protect their secrets, attempt to uncover theiropponent's secrets, or both.

Various game components are available to the players in forming theirarsenals. The game components may be divided into various categoriessuch as: secondary, or controlled, character pieces, effect pieces andobject pieces. Secondary or controlled character pieces typicallyrepresent characters that are playing in the game (i.e. warriors,athletes, magicians, etc.) Effect pieces typically perform one or moreactions that affect other pieces in the game. Object pieces typicallyrepresent some object that may be used in the game. Of course it will beappreciated that additional or alternative categories of components maybe utilized.

According to the above-described espionage-themed game, the gamecomponents may include agents (secondary pieces), plans (effect pieces)and devices (object pieces). Each agent piece represents an operative.Once deployed, the operative stays in play until captured by theopponent. Agents may be deployed during a player's turn. Agents arecapable of infiltrating or securing secrets.

Each plan piece has an effect on other pieces in play. The plan piecemay be moved to an “inactive area” (described below) after it isexecuted.

Each device piece represents a piece of technology or other artifactthat may be used against an opponent. Devices may be deployed during aplayer's turn, but may be activated at any time.

Each game component will typically include a variety of indiciaindicating information about the game component. This information mayinclude, for example, the component's category (i.e. secondary, effect,or object), conditions under which the component may be brought intoplay, effects and/or abilities. The information may be indicated in anymeaningful way, including by pictures, words, colors, etc.

An exemplary game component useful for the espionage-themed game isshown in FIG. 6. As shown in FIG. 6, the depicted game componentincludes indicia corresponding to: Piece Name; Deployment Cost; PieceType; Manifest Rating; Piece Abilities; Infiltrate/Elude,Observe/Secure; and Activity Points.

As might be expected, the Piece Name indicates the name of theindividual piece.

The Deployment Cost represents the amount of money which must bebudgeted to deploy the piece. Deployment Cost is expressed inInternational Currency (IC).

The Piece Type specifies whether the piece is an agent, device, or plan.

The Manifest Rating is a number indicating the relative availability ofthe piece. A higher number indicates that the piece is more available.Generally, the manifest rating will equal the percentage chance that apiece will manifest (i.e. be made available for play) during a giventurn. (This is described in greater detail below.)

Piece Abilities lists the actions the particular piece can take. Forpieces that are capable of moving between zones (see below) the movementcosts may either be identified on the card, or assumed for each piecetype, i.e. all agents may have a predetermined movement cost while alldevices may have a different predetermined movement cost, both of whichare assumed and not identified on the particular playing piece.

Infiltrate/Elude, Observe/Secure represents agent ratings. Each agentreceives four ratings. The first two ratings, Infiltrate and Elude,reflect the agent's capability to enter behind enemy lines and discoverenemy secrets. The second two ratings, Observe and Secure, reflect anagent's ability to protect secrets.

Activity points are illustrated by a bar on the right side of theplaying piece. The bar represents the number of activity points thepiece currently has at its disposal. An agent, device, or plan maytrigger abilities once they have accrued a certain number of activitypoints. A piece may not accrue more than 8 activity points.

As mentioned above, each player may design his or her own unique arsenalof playing components. The set of cards from which the player's arsenalmay be designed is determined by the primary and secondary traits orfoci selected by the player. The number of game components that may beincluded in the arsenal may be limited according to the game rules. Forexample, one embodiment of the presently described game may limit thenumber of game components to 50. Of course it will be appreciated thatthe game rules may impose any type of upper or lower limit on the numberof game components in an arsenal, or impose no limit at al.

The playing field may incorporate a number of different zones. The zonesmay have different characteristics, for example, placement in differentzones may indicate whether a game component is in use, available foruse, or not available for use. In addition, game components located insome zones may not be visible to one or more players.

In the espionage-themed game described above, each player controls aplaying field having seven different zones: an Arsenal Zone, anActivated Zone, a Deployed Zone, three Secret Zones, and an InactiveZone. An exemplary game set up is shown in FIG. 7.

The Arsenal Zone is the starting point for all pieces in the game. TheArsenal represents the group of actively cultivated contacts, researchprograms, and other tools. Pieces in the arsenal may not be seen byeither player.

The Activated Zone includes pieces that are ready for play (i.e.available for use). Pieces move from the Arsenal Zone to the ActivatedZone based on their Manifest score (as described in greater detailbelow). Pieces in the Activated Zone may be deployed, when appropriate,by paying their Deployment Cost. Pieces in the Activated Zone may notexecute abilities, and do not accrue Activity Points. Pieces in theActivated Zone may be seen by their owner, but not by the opponent.However, an opponent is allowed to see how many pieces are in theActivated Zone.

The Deployed Zone includes pieces that have been put into play.Accordingly, these pieces can execute abilities and may be moved toeither the player's or the opponent's Secret Zones. Pieces in theDeployed zone may become visible to an opponent under certainconditions, but are typically hidden when they come into play. Anopponent may see that a piece has been deployed, but will not typicallybe able to see the details of the piece, including its type, cost,abilities, etc.

There are three Secret Zones for each player. Each Secret Zonerepresents one player objective. Pieces in the Secret zones can usetheir abilities and accrue Activity Points.

The Inactive Zone includes pieces that have been neutralized (typicallyagents or devices). Pieces in the inactive zone are visible to bothplayers, but have no Activity Points.

According to one method of playing the espionage-themed game, playerstake turns activating components, moving components to different zones,and engaging in battles. Each player's turn proceeds through a series ofstages: Manifest phase, Accrual phase, Main phase, and Attack phase.

During the Manifest phase pieces in the arsenal are checked to determinewhether or not they will manifest into the Activated Zone. As anexample, a piece in the Arsenal Zone that has a Manifest rating of 10will have a 10% chance of manifesting into the Activated Zone during anygiven Manifest Phase. A calculation is performed to determine whetherthe card successfully Manifests (i.e. whether on this particular turnthe card has beaten the odds and can be introduced into play). Thiscalculation may be performed, for example, by a computer program capableof simulating a probabilistic event. Those of skill in the art will befamiliar with the concept of pseudo-random number generation as a meansof simulating probabilistic events and any suitable means for doing somay be employed. Alternatively, the calculation could be performed bythe simple mechanism of rolling a die (i.e. for a card having a Manifestrating of 17, a roll of 1 on a six-sided die results in the cardManifesting while a role of 2, 3, 4, 5, or 6 results in the cardremaining in the Arsenal). Thus, it will be understood that on any giventurn, any number (or no) cards may be moved from a particular player'sArsenal Zone into the player's Activated Zone.

During the Accrual phase, the activity point total of each card isincremented by 1. Also, players receive additional cash (20,000IC, orInternational Currency) and interest (25%) on their unspent cash.

During the Main phase, activated pieces may be deployed by paying theirdeployment cost in cash. Agent pieces in the Deployed zone may be movedinto a Secret Zone and vice versa. A player can move his or her Agentpieces into any player-owned uncaptured Secret Zones at no cost. Agentpieces may be moved into opponent's ‘outermost’ Secret Zone at the costof two Activity Points. Pieces may use abilities.

During the Attack phase, any pieces that are in an opponent's zone placethat zone into contention. Battles take place in the following sequence:

-   1. The defending player, if they have pieces in the zone, may    voluntarily reveal any of those pieces that remain hidden. Pieces    that remain hidden may not participate in the defense of the zone.-   2. Players may use piece's abilities.-   3. The attacking player reveals all pieces he or she has in that    zone.-   4. Players may use piece's abilities.-   5. The Infiltrate ratings of all attacking pieces are totaled. The    Observe ratings of all revealed defending pieces are totaled. The    attacking player assigns Infiltrate points from his or her total to    revealed defending pieces as desired and the defending player    assigns Observe points from his or her total to any attacking    pieces, as desired. Attacking pieces that are assigned observe    points equal to their Elude ratings are captured, and defending    pieces that are assigned Infiltrate points equal to their Secure    rating are captured. After pieces are captured, if there are    attacking pieces still present in the zone, and no remaining    revealed defending pieces in the zone, the attacker captures the    zone, and all pieces in that zone return to their owner's arsenals.

As stated above, the presently-described game provides level advancementgame play. An example of level advancement game play in the context ofthe espionage-theme game allows players to advance in two ways:

First, players may advance by earning renown points whenever they win agame. When a player reaches a certain renown point total, the playerwill achieve a new renown level. At each successive renown level, accessto certain pieces will be unlocked. Players earn more renown fordefeating a player above their level. Players may also lose renownpoints if they lose a match to a player who is below their level.

Second, players receive additional “contacts” by playing games. Duringeach game, depending on a player's performance, he or she will receive avarying number of new contacts, represented by game pieces. At level 1,for example, a winning player may receive 2 new contacts. A losingplayer may receive 1 new contact. These contact pieces are randomlyselected from the pieces unlocked for that player based on his or herselection of primary and secondary foci.

According to one method of play, player matches are assigned at randomand a player must play randomly assigned opponents at a renown levelequal to or below their own. Additionally, players may elect to raisethe ceiling on the highest level opponent they may be randomly assigned.

As stated above, a GBE employing an REU calculation may be employed tobalance and maintain balance of the above-described game. According toone method, REU is first calculated for a given player, for a given gamewin, for a given component in order to determine the expected value ofusage for a given component. This can be calculated in the followingmanner:REU=O*A/NWhere:

-   A (player p, game g)=the number of unique components in that    player's arsenal;-   O (player p, game g, component c)=the probability that a player at    this exact experience level AND with access to the component    (ignoring any class distinctions), owns at least one of component c;    and-   N (player p, game g)=the expected number of unique components owned    by that player.-   “A” is determined by tracking and counting the actual number of    unique components played by this particular game winning arsenal.    “A” takes into account the fact that some players will tend to use    50 unique components, while other players will tend to use only 10    unique components.-   “O” is the probability of owning a particular component, assuming    the player is in the class and is therefore equal to 1 minus the    probability that the player owns none of those particular    components:    O=Prob(own>=1)=1−Prob(own=0)

Prob(own=0) can be calculated by multiplying together every chance theplayer had to not get the particular component:Prob(own=O)=((1−C)/C)^(T)where:

-   C=the count of components available to each class from the set this    component is part of; and-   T=the total number of components this player has acquired from that    set.    Thus,    O=1−((1−C)/C)^(T)    For a given set, the expected total number of components owned is:    T*O    N is the sum of expected owned components over all the sets, so:    N=Σ(T _(i) *O _(i))    i over all sets    So:    REU=A*(1−((1−C)/C)^(T))/Σ(T _(i) *O _(i))

Once REU is calculated, the GBE can monitor the actual usage (U), degreeof success (S) and REU for each component and determine a Balance Rating(BR) for each component.

Balance Rating can be calculated in several different ways. Exemplarymethods for calculating BR are illustrated below:${{BR}_{1}\lbrack{component}\rbrack} = {\sum\limits_{{all}\quad{players}}\left( {S*{U/{REU}}} \right)}$or${{BR}_{2}\lbrack{component}\rbrack} = {\sum\limits_{{all}\quad{players}}{\left( {S*U} \right)/{\sum\limits_{{all}\quad{players}}({REU})}}}$

In addition, the above calculations can be normalized by the sum ofsuccess of all players. Exemplary methods for calculating a normalizedBR are illustrated below.${{BR}_{1}{{Norm}\lbrack{component}\rbrack}} = {\sum\limits_{{all}\quad{players}}{\left( {S*{U/{REU}}} \right)/{\sum\limits_{{all}\quad{players}}(S)}}}$or${{BR}_{2}{{Norm}_{1}\lbrack{component}\rbrack}} = {\sum\limits_{{all}\quad{players}}{\left( {S*U} \right)/{\sum\limits_{{all}\quad{players}}\left( {S*{REU}} \right)}}}$or${{BR}_{2}{{Norm}_{2}\lbrack{component}\rbrack}} = {\left\lbrack {\sum\limits_{{all}\quad{players}}{\left( {S*U} \right)/{\sum\limits_{{all}\quad{players}}({REU})}}} \right\rbrack/{\sum\limits_{{all}\quad{players}}(S)}}$

In the case where an exact EU is used for REU, a normalized BalanceRating can provide the degree of over (or under) use of the component.Specifically, a normalized BR of 1 means the component is used exactlyas it would be in a hyper-balanced game, a normalized Balanced Rating of0.5 means that the component is used half as much as it would be in ahyper-balanced game, and a normalized BR of 4 means the component isbeing used 4 times as much.

Alternatively, a Balanced Range can be calculated by identifying anacceptable deviation from a summary statistic, such as the mean, median,or a specific percentile (e.g. 30% percentile, 35% percentile, 40%percentile, 45% percentile, etc.) of the components' balance ratings. Ofcourse, any other suitable method of determining an acceptable balancedrange may be employed. Components outside of the acceptable balancedrange may then be adjusted, as described above.

It will be appreciated that this specific calculation for theabove-described game can be extended to all types of games, where, foreach game one must initially determine how to accurately calculate thesuccess weighting (S) for each given player, the REU for each givenplayer for each given component, and the actual usage (U) for each givenplayer for each given component. The success weighting may be the numberof game wins, the number of experience points earned, or some othercalculation of success as determined by the specific game. In theabove-described game, S is the number of game wins, REU is calculated inthe manner described above, and U is the fraction of the player's winswhere the given component was in the arsenal.

As above, Balanced Range can then be calculated and any componentsoutside of the acceptable limits may then be adjusted.

It will be appreciated that one or more GBEs may be employed to balancea particular game. For example, where the game includes multipleindependent component sets, a separate GBE may be employed for each set.For the purposes of the present disclosure, a “component set” includesgame components between which a player may choose during the course of agame. An example of game components that would be included in a singlecomponent set are a weapon available for purchase and a skill availablefor purchase, where the weapon and skill can be purchased with the sametype of currency (e.g. both the weapon and skill can be purchased withgold), or where one type of currency can be purchased/obtained by usinganother (i.e. the weapon can only be purchased with gold and the skillcan only be purchased with skill points, but skill points can bepurchased with gold). Components are considered to be in independentcomponent sets if there is no way for a player to choose between thetwo, in other words, if the components are not tradable within thecontext of the game. An example of components in independent componentsets would be weapons that can only be purchased with gold and skillsthat only be purchased with skill points where gold and skill pointscannot be traded for one another.

Those familiar with gaming will be aware that many games can be playedin multiple formats (or metagames), with each format employing some orall of the same game components, but often employing different rules.For example, the game Magic: The Gathering (Wizards of the Coast,Seattle, Wash.) is known to have at least three formats: a sealed deckformat, often used in tournaments, where players are provided with aspecific pool of cards from which they must build their personalizeddeck; a type II format, where players may include in their personalizeddecks any cards published in the last 6 sets of cards released by thegame manufacturer; and a type I format, where players may include intheir personalized decks any card ever released by the gamemanufacturer.

In the case that a game can be played in one of a number of differentformats, it will be understood that it would be desirable to ensure thatthe game components are in balance regardless of the format of game inwhich they are used. However, it may often be the case that a componentthat is in balance in one format is out of balance in another, resultingin a format-dependent imbalance. One way to compensate forformat-dependent imbalance is to employ individual GBEs for each format,and then have the individual GBEs communicate to make decisions aboutwhether and how to adjust a particular component when the component isidentified as being out of balance.

As a non-limiting example, each Magic format described above may beregulated by an individual GBE. When the individual GBEs identifyout-of-balance components, they may alert one another of the imbalanceand adjust the identified out-of-balance components as follows:

If a particular component is found to be too weak in all formats, thecomponent can be made stronger.

If the component is too strong in any format, the component can be madeweaker.

If the component is too weak in one or more formats, but withinacceptable parameters in any format, the component is left as is.

Of course it will be appreciated that alternative methods of adjustingidentified format-dependent imbalance may be employed.

Moreover, the multiple metagame balancing technique described above maybe employed not just when a game exists in multiple formats, but alsowhen a particular game is played differently by different types ofplayers. For example, different GBEs may be employed to monitor how thegame and components are played by players of different experiencelevels. This may be desirable in the context of a game where aparticular component is very valuable to beginners, less valuable toexperienced players, and then regains importance for very experiencedplayers. Moreover, it will be appreciated that multiple GBEs may beemployed to monitor individual metagames distinguished by the gamedesigner's subjective preference.

It is believed that the disclosure set forth above encompasses multipledistinct inventions with independent utility. While each of theseinventions has been disclosed in its preferred form, the specificembodiments thereof as disclosed and illustrated herein are not to beconsidered in a limiting sense as numerous variations are possible. Thesubject matter of the inventions includes all novel and non-obviouscombinations and subcombinations of the various elements, features,functions and/or properties disclosed herein. Similarly, where thedisclosure refers to “an” element or the equivalent thereof, suchdisclosure should be understood to include incorporation of one or moresuch elements, neither requiring nor excluding two or more suchelements.

Inventions embodied in various combinations and subcombinations offeatures, functions, elements and/or properties may be claimed in arelated application. Such claims, whether they are directed to adifferent invention or directed to the same invention, whetherdifferent, broader, narrower or equal in scope to any original claims,are also regarded as included within the subject matter of theinventions of the present disclosure.

1. A computer readable storage medium for use with a multi-component computer game, the computer readable storage medium comprising: code for calculating actual usage of a game component within the computer game; code for identifying an acceptable usage range for each game component; and code for determining whether the actual usage of the game component is within the acceptable usage range.
 2. The computer readable storage medium of claim 1 further comprising code for identifying the game component as out-of-balance when the calculated actual usage is outside of the acceptable usage range.
 3. The computer readable storage medium of claim 2 further comprising code for weighting actual usage by degree of success.
 4. The computer readable storage medium of claim 3 wherein weighting actual usage by degree of success comprises identifying the actual usage by a given player and identifying the player's success in the computer game.
 5. The computer readable storage medium of claim 4 where identifying the player's success in the computer game comprises determining if the player won the game.
 6. The computer readable storage medium of claim 4 where identifying the player's success in the computer game comprises monitoring the player's progression through the game.
 7. The computer readable storage medium of claim 3 further comprising code for calculating relative expected usage.
 8. The computer readable storage medium of claim 1 further comprising code for automatically adjusting the game parameters when actual usage is outside of the acceptable usage range.
 9. The computer readable storage medium of claim 8 wherein the game component has a power level in the game and automatically adjusting the game parameters comprises altering the power level of the component.
 10. The computer readable storage medium of claim 9 wherein the game component has a cost and automatically adjusting the game parameters comprises altering the cost of the component.
 11. A method for identifying out-of-balance components in a computer game requiring players to make selections between multiple game components, the method comprising: determining an individual player's actual usage of a game component; calculating the player's relative expected usage of the game component; identifying the player's rate of success in the game; calculating a balance rating for a game component based on the players' actual usage, relative expected usage, and rate of success; determining whether the balance rating is within the acceptable usage range; and identifying the game component as being out-of-balance if the balance rating is outside of the acceptable usage range.
 12. The method of claim 11 further comprising altering the game if the component is identified as being out-of-balance.
 13. The method of claim 11 wherein calculating actual usage comprises identifying the component or components that are selected when a player selects between two or more components.
 14. The method of claim 13 wherein calculating actual usage further comprises identifying the component or components that are not selected when a player selects between two or more components.
 15. The method of claim 11 wherein calculating the player's relative expected usage of the game component comprises identifying and counting the number of unique components played by the player during the game.
 16. The method of claim 11 wherein calculating the player's relative expected usage of the game component comprises determining the probability of the player owning the game component.
 17. The method of claim 11 wherein calculating the player's relative expected usage of the game component comprises calculating the expected number of unique components owned by the player.
 18. The method of claim 11 further comprising normalizing the balance rating.
 19. The method of claim 11 wherein calculating the player's relative expected usage of the game component comprises mathematical analysis of a hypothetical hyper-balance game.
 20. A computer game optimization system comprising: a computer game including multiple game components; a first computer running the computer game; a game balancing engine in electronic communication with the first computer, the game balancing engine being configured to collect data regarding usage of the game components in the computer game and identify out-of-balance components based on the collected data.
 21. The computer game optimization system of claim 20 wherein the game balancing engine is further configured to automatically alter the game when out-of-balance components are identified.
 22. The computer game optimization system of claim 20 further comprising a plurality of computers running the computer game, wherein the game balancing engine is in electronic communication with the plurality of computers and the game balancing engine is configured to identify out-of-balance components based on data collected from the plurality of computers.
 23. A business method comprising: collecting data regarding player component selections by multiple players in a networked computer game; and maintaining a database of component selection information.
 24. The business method of claim 23 wherein maintaining a database of component selection information comprises identifying an actual usage of a component for a given player.
 25. The business method of claim 24 wherein maintaining a database of component selection information comprises identifying a degree of success for the player.
 26. The business method of claim 24 wherein maintaining a database of component selection information comprises identifying a relative expected usage of the component for the player.
 27. The business method of claim 23 further comprising calculating a balance rating for a component in the networked computer game.
 28. The business method of claim 27 further comprising comparing the balance rating for the component with an expected usage range for the component and identifying the component as out-of-balance if the balance rating is outside of the expected usage range.
 29. The business method of claim 23 where the data is collected in real time, as the game is played.
 30. The business method of claim 23 where the data is collected after the game has been released to the public.
 31. A computer game to be played by one or more players where the game comprises: multiple selectable components, where players select between at least two different components during game play; and a usage database configured to collect usage data and electronically communicate with a game balancing engine.
 32. A method for optimizing performance of a computer game employing multiple selectable game components and rules governing the cost and power associated with the use and acquisition of the components, the method comprising: identifying a current game state; hypothesizing a hypothetical game state in which all components are hyper-balanced; incrementally altering the rules so as to create an altered game state; and determining whether the altered game state more closely resembles the hypothetical game state than the current game state.
 33. The method of claim 32 wherein identifying a current game state comprises monitoring game play by multiple game players and calculating each player's actual usage for a component.
 34. The method of claim 33 wherein identifying a current game state further comprises calculating each player's rate of success in the game.
 35. The method of claim 34 wherein identifying a current game state further comprises calculating a balance rating for the components.
 36. The method of claim 35 further comprising determining an acceptable balance range for the component.
 37. The method of claim 36, where the acceptable balance range is determined by identifying an acceptable deviation from a hyper-balanced balance rating.
 38. The method of claim 36, further comprising determining an acceptable balance range for the component.
 39. A computer readable storage medium for optimizing performance of a computer game employing multiple selectable game components and rules governing the cost and power associated with the use and acquisition of the components, the computer readable storage medium comprising: code for identifying a current game state; code for hypothesizing a hypothetical game state; code for incrementally altering the rules so as to create an altered game state; and code for determining whether the altered game state more closely resembles the hypothetical game state than the current game state.
 40. The computer readable storage medium of claim 39 wherein the code for identifying a current game state comprises code for monitoring game play by multiple game players and code for calculating each player's actual usage for a component.
 41. The computer readable storage medium of claim 40 wherein the code for identifying a current game state further comprises code for calculating each player's rate of success in the game.
 42. The computer readable storage medium of claim 41 wherein the code for identifying a current game state further comprises code for calculating a balance rating for the component.
 43. The computer readable storage medium of claim 42 further comprising code for determining an acceptable balance range for the component.
 44. The computer readable storage medium of claim 43, where the acceptable balance rating range is determined by identifying an acceptable deviation from a hyper-balanced balance rating.
 45. The method of claim 43, where the acceptable balance range is determined by identifying an acceptable deviation from a summary statistic of the components' balance ratings. 